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American Sign Language Detection using PCA and LDA

We now examine the differences between LDA and QDA. (a) If the Bayes decision boundary is linear, do we expect LDA or QDA to perform better on the training set? On the test set? (b) If the Bayes decision boundary is non-linear, do we expect LDA or QDA to perform better on the training set? On the test set? (c) In general, as the sample size n increases, do we expect the test prediction accuracy of QDA relative to LDA to improve, decline, or be unchanged? Why? (d) True or False: Even if the Bayes

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American Sign Language Detection using PCA and LDA

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